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Conversational analytics rarely fails because of technology. It fails when leadership habits don't change. Why culture decides success more than AI capability.
In this demo, we show how Codd AI transforms NetSuite data into trusted, AI-powered analytics using an automated semantic layer and governed metrics. See how technical data and business knowledge come together to automatically generate ontologies, data models, and certified metrics — enabling business users to ask questions in natural language, run deeper analysis, and get consistent answers across tools.
GenAI analytics is moving from experiment to infrastructure. Ten predictions on how it will change in 2026, and what they mean for data and analytics leaders.
The term semantic layer has been stretched until it means almost nothing. Why the real divide is between universal and domain-specific approaches to context.
A practical guide to the build vs buy decision for AI-powered analytics: what it really takes to build your own system versus buying a purpose-built platform.
When to fine-tune an LLM and when to invest in context engineering with semantic layers and RAG, and why the most successful enterprise AI strategies use both.
Why context-aware AI is essential for trustworthy GenAI analytics, and why organizations must standardize business context now, before AI fragments it further.
Why every data and AI vendor is now building a semantic layer, how the approaches differ, and why most semantic layer tools fall short of enterprise needs.
ChatGPT and copilots like Databricks Genie are useful, but without enterprise context they guess. Why the next frontier is context-aware, business-fluent AI.